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. The postdoc will develop machine learning algorithms to analyze phenotype and sequence data, as well as active learning algorithms to optimize and control experiments in directed evolution. This position
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phases. This research will integrate a variety of modeling tools across multiple time and length scales to predict the microstructure evolution during the AM build process and post build thermal
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problems, including ensuring the reliability of our nation’s infrastructure, development of methods for storage and transport of alternative fuels, and development of critical data on radiation’s effects
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RAP opportunity at National Institute of Standards and Technology NIST Development of a Digital Twin Framework for Metal Additive Manufacturing Location Material Measurement Laboratory
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been revisited in decades; our goal is to develop a suite of suitable statistical tools which allow clock scientists to properly analyze data with gaps. Additionally, we aim to provide comprehensive
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RAP opportunity at National Institute of Standards and Technology NIST Development of New Computational Methodologies for Molecular Simulation of Soft Materials Location Material Measurement
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environmentally controlled facilities for accurate measurement of 1-D and 2-D length, diameter, flatness, straightness, roundness, complex form, angle, and laser frequency. We are interested in efforts that develop
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, this project will employ emerging proteomics techniques (such as data-independent acquisition) and will be working alongside software and algorithm developers to ensure that these platforms can be used beyond
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RAP opportunity at National Institute of Standards and Technology NIST Analytical Methods Development for Metabolomics Location Material Measurement Laboratory, Biomolecular Measurement Division
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of the constraints on sequencing (read length, depth), and informatics (e.g., database composition, algorithm biases). Proposals should address these challenges with strategies to evaluate the metagenomic